Values Conflict & Behavioural Drift 2026 (Dataset, n = 349)

This dataset is part of the Human Clarity Institute’s AI–Human Experience 2026 data series. It examines tensions between individuals’ stated personal values and their real-world behaviours when using digital and AI systems, including patterns of behavioural persistence despite misalignment, resistance versus resignation, normalisation of drift over time, and decision intervention thresholds in AI-assisted contexts.

The dataset includes:
• validated 1–7 Likert-scale items
• measures of perceived values–behaviour misalignment and behavioural normalisation
• behavioural indicators of resistance, override frequency, and decision intervention thresholds
• multi-select variables stored as canonical semicolon-delimited snake_case tokens
• open-text reflections with minimal safe cleaning (trim + newline removal only)
• demographic variables across six English-speaking countries
• digital life exposure (daily hours online) and AI-tool usage frequency

Data were collected on 10 February 2026 via Prolific from adults in the UK, US, Australia, Canada, New Zealand, and Ireland.
All data were cleaned, anonymised, and processed under the Human Clarity Institute’s machine-readable dataset protocol, which includes:

• canonical snake_case variable naming
• validated numeric ranges
• standardised multi-select formats
• minimal safe text cleaning
• full alignment with the accompanying data dictionary
• removal of Prolific IDs and timestamps
• SHA-256 checksums for all files

This dataset contributes to understanding how digitally active adults experience and respond to behavioural drift under AI influence, supporting longitudinal tracking of values–behaviour alignment, resistance dynamics, and decision reliance patterns in the evolving cognitive relationship between humans and AI in everyday life.